Globally, intimate partner violence is one of the major health problems women face every day. Its consequences are enormous. However, our search of the available literature revealed that no study had examined the spatial distribution of intimate partner violence and the predictors of intimate partner violence among women in Nigeria using current nationally representative data. This study, therefore, sought to examine the spatial distribution of intimate partner violence and its predictors among women in Nigeria. We sourced data from the 2018 Nigeria Demographic and Health Survey for this study. A sample size of 8,968 women was considered for this study. We employed both multilevel and spatial analyses to ascertain the factors associated with intimate partner violence and its spatial clustering. The hot spot areas for intimate partner violence in Nigeria were Gombe, Bauchi, Adamawa, Plateau, Kogi, Edo, Ebonyi, and Rivers. The likelihood of experiencing intimate partner violence
Leprosy incidence remained at around 200,000 new cases globally for the last decade. Current strategies to reduce the number of new patients include early detection and providing post-exposure prophylaxis (PEP) to at-risk populations. Because leprosy is distributed unevenly, it is crucial to identify high-risk clusters of leprosy cases for targeting interventions. Geographic Information Systems (GIS) methodology can be used to optimize leprosy control activities by identifying clustering of leprosy cases and determining optimal target populations for PEP. The geolocations of leprosy cases registered from 2014 to 2018 in Pasuruan and Pamekasan (Indonesia) were collected and tested for spatial autocorrelation with the Moran’s I statistic. We did a hotspot analysis using the Heatmap tool of QGIS to identify clusters of leprosy cases in both areas. Fifteen cluster settings were compared, varying the heatmap radius (i.e., 500 m, 1000 m, 1500 m, 2000 
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Background
Anemia is a global public health problem, particularly in developing countries. Assessing the geographic distributions and determinant factors is a key and crucial step in designing targeted prevention and intervention programmes to address anemia. Thus, the current study is aimed to assess the spatial distribution and determinant factors of anemia in Ethiopia among adults aged 15–59.
Methods
A secondary data analysis was done based on 2016 Ethiopian Demographic and Health Surveys (EDHS). Total weighted samples of 29,140 adults were included. Data processing and analysis were performed using STATA 14; ArcGIS 10.1 and SaTScan 9.6 software. Spatial autocorrelation was checked using Global Moran’s index (Moran’s I). Hotspot analysis was made using Gettis-OrdGi statistics. Additionally, spatial scan statistics were applied to identify significant primary and secondary cluster of anemia. Mixed effect ordinal logistics were fitted to determine factors associated with th